IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v14y2022i3p1243-d731127.html
   My bibliography  Save this article

Analysis of Risky Driving Behavior of Urban Electric Bicycle Drivers for Improving Safety

Author

Listed:
  • Dan Zhou

    (School of Architecture and Transportation Engineering, Guilin University of Electronic Technology, Guilin 541004, China)

  • Mengying Chang

    (School of Architecture and Transportation Engineering, Guilin University of Electronic Technology, Guilin 541004, China)

  • Guobin Gu

    (School of Architecture and Transportation Engineering, Guilin University of Electronic Technology, Guilin 541004, China)

  • Xin Sun

    (School of Architecture and Transportation Engineering, Guilin University of Electronic Technology, Guilin 541004, China)

  • Huizhi Xu

    (School of Traffic and Transportation, Northeast Forestry University, Harbin 150040, China)

  • Wenhan Wang

    (School of Architecture and Transportation Engineering, Guilin University of Electronic Technology, Guilin 541004, China)

  • Tao Wang

    (School of Architecture and Transportation Engineering, Guilin University of Electronic Technology, Guilin 541004, China)

Abstract

In this work, to clarify the impact of electric bicycle drivers’ risky driving behavior on driving safety, we used multiple regression analysis methods combined with a questionnaire survey of residents of the city of Guilin, China. We studied the impact of the two dimensions of safety knowledge and safety attitude on risky driving behavior, and identified the differences in the impact of these two dimensions from the perspective of personal characteristics. Through modeling analysis, we found that “responsible attitude” and “group behavior attitude” explain 62.4% of the variation in aggressive behavior; 48.5% of the variation in negligent behavior is caused by “age”, “safety knowledge” and “responsible attitude”; and 52% of the variation in violations is caused by “age”, “violation attitude” and “group behavior attitude”. The results show that “group behavior attitude” affects the occurrence of aggression; that safety knowledge has a significant negative impact on unintentional negligence but has no significant effect on deliberate violations and aggression; and that the difference in risky driving behavior is mainly manifested in “age”, “gender”, “violation” and “accident experience”.

Suggested Citation

  • Dan Zhou & Mengying Chang & Guobin Gu & Xin Sun & Huizhi Xu & Wenhan Wang & Tao Wang, 2022. "Analysis of Risky Driving Behavior of Urban Electric Bicycle Drivers for Improving Safety," Sustainability, MDPI, vol. 14(3), pages 1-19, January.
  • Handle: RePEc:gam:jsusta:v:14:y:2022:i:3:p:1243-:d:731127
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/14/3/1243/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/14/3/1243/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Elliot Fishman & Christopher Cherry, 2016. "E-bikes in the Mainstream: Reviewing a Decade of Research," Transport Reviews, Taylor & Francis Journals, vol. 36(1), pages 72-91, January.
    2. Xingchen Yan & Tao Wang & Xiaofei Ye & Jun Chen & Zhen Yang & Hua Bai, 2018. "Recommended Widths for Separated Bicycle Lanes Considering Abreast Riding and Overtaking," Sustainability, MDPI, vol. 10(9), pages 1-16, September.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Manja Hoppe Andreasen & Jytte Agergaard & Lasse Møller-Jensen & Martin Oteng-Ababio & Gerald Albert Baeribameng Yiran, 2022. "Mobility Disruptions in Accra: Recurrent Flooding, Fragile Infrastructure and Climate Change," Sustainability, MDPI, vol. 14(21), pages 1-19, October.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Tao Wang & Sihong Xie & Xiaofei Ye & Xingchen Yan & Jun Chen & Wenyong Li, 2020. "Analyzing E-Bikers’ Risky Riding Behaviors, Safety Attitudes, Risk Perception, and Riding Confidence with the Structural Equation Model," IJERPH, MDPI, vol. 17(13), pages 1-18, July.
    2. Ziwen Ling & Christopher R. Cherry & John H. MacArthur & Jonathan X. Weinert, 2017. "Differences of Cycling Experiences and Perceptions between E-Bike and Bicycle Users in the United States," Sustainability, MDPI, vol. 9(9), pages 1-18, September.
    3. Gu, Tianqi & Kim, Inhi & Currie, Graham, 2019. "To be or not to be dockless: Empirical analysis of dockless bikeshare development in China," Transportation Research Part A: Policy and Practice, Elsevier, vol. 119(C), pages 122-147.
    4. Ton, Danique & Duives, Dorine, 2021. "Understanding long-term changes in commuter mode use of a pilot featuring free e-bike trials," Transport Policy, Elsevier, vol. 105(C), pages 134-144.
    5. Li, Hongwei & Zhong, Xin & Zhang, Wenbo & Li, Sulan & Xing, Yingying, 2020. "An algorithm for e-bike equivalents at signalized intersections based on traffic conflict events number," Transportation Research Part A: Policy and Practice, Elsevier, vol. 134(C), pages 78-95.
    6. Zhang, Ziru & Krishnakumari, Panchamy & Schulte, Frederik & van Oort, Niels, 2023. "Improving the service of E-bike sharing by demand pattern analysis: A data-driven approach," Research in Transportation Economics, Elsevier, vol. 101(C).
    7. Sun, Shan & Guo, Liang & Yang, Shuo & Cao, Jason, 2024. "Exploring the contributions of Ebike ownership, transit access, and the built environment to car ownership in a developing city," Journal of Transport Geography, Elsevier, vol. 116(C).
    8. Wafa Elias & Victoria Gitelman, 2018. "Youngsters’ Opinions and Attitudes toward the Use of Electric Bicycles in Israel," Sustainability, MDPI, vol. 10(12), pages 1-16, November.
    9. Nils Hooftman & Luis Oliveira & Maarten Messagie & Thierry Coosemans & Joeri Van Mierlo, 2016. "Environmental Analysis of Petrol, Diesel and Electric Passenger Cars in a Belgian Urban Setting," Energies, MDPI, vol. 9(2), pages 1-24, January.
    10. Liu, Yixiao & Tian, Zihao & Pan, Baoran & Zhang, Wenbin & Liu, Yunqi & Tian, Lixin, 2022. "A hybrid big-data-based and tolerance-based method to estimate environmental benefits of electric bike sharing," Applied Energy, Elsevier, vol. 315(C).
    11. Yongqiang Zhang & Zhuang Hu & Min Zhang & Wenting Ba & Ying Wang, 2022. "Emergency Response Resource Allocation in Sparse Network Using Improved Particle Swarm Optimization," IJERPH, MDPI, vol. 19(16), pages 1-11, August.
    12. Oliver Schubert-Olesen & Jens Kröger & Thorsten Siegmund & Ulrike Thurm & Martin Halle, 2022. "Continuous Glucose Monitoring and Physical Activity," IJERPH, MDPI, vol. 19(19), pages 1-20, September.
    13. Jurgis Zagorskas & Marija Burinskienė, 2019. "Challenges Caused by Increased Use of E-Powered Personal Mobility Vehicles in European Cities," Sustainability, MDPI, vol. 12(1), pages 1-13, December.
    14. Jadwiga Biegańska & Elżbieta Grzelak-Kostulska & Michał Adam Kwiatkowski, 2021. "A Typology of Attitudes towards the E-Bike against the Background of the Traditional Bicycle and the Car," Energies, MDPI, vol. 14(24), pages 1-21, December.
    15. Eccarius, Timo & Leung, Abraham & Shen, Chung-Wei & Burke, Matthew & Lu, Chung-Cheng, 2021. "Prospects for shared electric velomobility: Profiling potential adopters at a multi-campus university," Journal of Transport Geography, Elsevier, vol. 96(C).
    16. Cheng Wang & Liyang Wei & Kun Wang & Hongya Tang & Bo Yang & Mengfan Li, 2022. "Investigating the Factors Affecting Rider’s Decision on Overtaking Behavior: A Naturalistic Riding Research in China," Sustainability, MDPI, vol. 14(18), pages 1-18, September.
    17. Sławomir Dorocki & Dorota Wantuch-Matla, 2021. "Power Two-Wheelers as an Element of Sustainable Urban Mobility in Europe," Land, MDPI, vol. 10(6), pages 1-25, June.
    18. Georgios Grigoropoulos & Seyed Abdollah Hosseini & Andreas Keler & Heather Kaths & Matthias Spangler & Fritz Busch & Klaus Bogenberger, 2021. "Traffic Simulation Analysis of Bicycle Highways in Urban Areas," Sustainability, MDPI, vol. 13(3), pages 1-25, January.
    19. Moyano, Amparo & Solís, Eloy & Díaz-Burgos, Elena & Rodrigo, Alejandro & Coronado, José M., 2023. "Typologies of stations’ catchment areas in metropolitan urban peripheries: From car-oriented to sustainable urban strategies," Land Use Policy, Elsevier, vol. 134(C).
    20. Hallberg, Martin & Rasmussen, Thomas Kjær & Rich, Jeppe, 2021. "Modelling the impact of cycle superhighways and electric bicycles," Transportation Research Part A: Policy and Practice, Elsevier, vol. 149(C), pages 397-418.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:14:y:2022:i:3:p:1243-:d:731127. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.